There are many ways to encode high definition television (HDTV) signals. These techniques can generally be classified as waveform coding, transform coding and vector quantization techniques.
Waveform coding techniques such as pulse code modulation (PCM) typically use a scalar quantizer to quantize analog samples. Additional steps may be employed to reduce the information that must be transmitted, such as sending only the difference of PCM samples, such a technique is known as differential PCM, or DPCM. Waveform coding is generally simple to implement, but not very efficient as far as bandwidth compression is concerned. An example of waveform coding is the KDD/Canon 140 Mbit/s HDTV Codec.
The transform coding techniques transform the image samples to the transform domain, achieving energy compaction. Scalar quantizers are designed for each individual coefficient depending on its energy and the sensitivity of the human visual system (HVS) to that coefficient. Most popular video coding systems at this time are based on variations of the Discrete Cosine Transform (DCT). Well designed transform algorithms achieve effective bandwidth compression while preserving good image quality. Examples of transform technique based codecs are Telettra's 68 Mbit/s HDTV codec and General Instruments's 15 Mbit/s Digi-Cipher HDTV codec.
Sub-band coding is a coding technique which divides the HDTV signal into many small bands. As most of the signal energy is concentrated in the low-frequency bands, more information bits are allocated to the samples in the low-frequency bands. Also, different bands have different signal characteristics, and so different techniques can be employed to encode each individual sub-band. Examples of sub-band coding include the 140 Mbit/s codecs by Bellcore and NTT.
Waveform coding, transform coding, and to some extent, sub-band coding are "symmetrical" algorithms in the sense that the complexity of the encoder and decoder is about equal. For most of the video transmission and storage applications, there is a far greater number of decoders required than there is encoders, because each receiver must have a decoder but only the broadcaster need have an encoder. Therefore, "symmetrical" algorithms may not offer the best solution from an overall system cost standpoint.
Vector quantization (VQ) basically quantizes a group of samples at one time. VQ has the advantage that only a table look-up operation is needed to decode the signal, leading to an extremely simple decoder. However, it generally suffers from relatively poor quality. In addition, the encoder, which must search through a codebook to find the best vector to represent a group of samples, is generally very computationally intensive. For high-quality television signals, HDTV in particular, real-time encoding requires extremely complicated hardware. Examples of vector quantization are disclosed in copending, commonly assigned applications Ser. Nos. 07/732,024, abandoned, and 07/759,361, which are herein incorporated by reference.